Signal-noise support vector model of a microwave transistor

Güneş, Filiz; Türker, Nurhan; Gürgen, Fikret

doi:10.1002/mmce.20239

Cited by 38 publications

(41 citation statements)

References 15 publications

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“…To evaluate the quality of the fit to target data and to make comparison between the SVRM and neural models, the following error terms are found to be convenient as in [4]:…”

Section: Error Analysis For the Black-box Modelsmentioning

confidence: 99%

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Knowledge-Based Support Vector Synthesis of the Microstrip Lines

Tokan

Güneş²

2009

PIER

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Abstract-In this paper, we proposed an efficient knowledge-based Support Vector Regression Machine (SVRM) method and applied it to the synthesis of the transmission lines for the microwave integrated circuits, with the highest possible accuracy using the fewest accurate data. The technique has integrated advanced concepts of SVM and knowledge-based modeling into a powerful and systematic framework. Thus, synthesis model as fast as the coarse models and at the same time as accurate as the fine models is obtained for the RF/Microwave planar transmission lines. The proposed knowledge-based support vector method is demonstrated by a typical worked example of microstrip line. Success of the method and performance of the resulted synthesis model is presented and compared with ANN results.

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“…To evaluate the quality of the fit to target data and to make comparison between the SVRM and neural models, the following error terms are found to be convenient as in [4]:…”

Section: Error Analysis For the Black-box Modelsmentioning

confidence: 99%

“…Furthermore, SVM is based on small sample statistical learning theory, whose optimum solution is based on limited samples instead of infinite sample that ensures enormous computational advantages. Typical applications of the SVRM to the microwave modeling can be found in [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Knowledge-Based Support Vector Synthesis of the Microstrip Lines

Tokan

Güneş²

2009

PIER

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“…1 which consists of the two main parts: (i) The first part is "The Data-Based Soft" model of the device which needs some amount of data to be established. In this part, linear learning machines such as neural network [5], or support vector machine [6] can be employed; (ii) The second part is 'the Circuit Analyze-Based' model whose fundamentals are given in the previous subsection. So PDSs can be obtained from the interrelations among the physically realizable performance triplets and terminations over a defined operation bandwidth B, expressed as follows:…”

Section: Performance Data Sheetsmentioning

confidence: 99%

“…1: (i) Firstly, a Soft-Model of the transistor which may be either Neural [5] or Support Vector model [6], is generated to determine the signal and noise behaviors within the whole operation domain of the device consisting of the configuration type (CT), the bias condition V DS , I DS , the operation frequency f ; (ii) Secondly, noise, input VSWR, gain performance of the device is characterized point by point within the operation domain as given in the works [7,8]; (iii) Finally, the Performance Data Sheets (PDS) can be obtained as resulted from the Gain-Bandwidth limitations [9] using the performance characterization of the active device.…”

Section: Introductionmentioning

confidence: 99%

A Generalized Design Procedure for a Microwave Amplifier: A Typical Application Example

Güneş¹,

Bilgin²

2008

PIER B

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Abstract-In this work, a generalized procedure is carried out for the design of a microwave amplifier. First of all, the Performance Data Sheets (PDS) resulted from the active device characterization are used as Feasible Design Target Space (FDTS). Employing the PDS, the compatible (Noise F , Input VSWR V i , Gain G T ) is determined over the predetermined bandwidth B between f min and f max operation frequencies with the source Z S and load Z L terminations as the design target. In the design stage, the Simplified Real Frequency Technique (SRFT) is utilized in the scattering-parameter formulation of the front-and back-end matching two-ports to provide the source and load terminations to the transistor, respectively. As an application example, a novel high technology transistor is chosen and the design targets are determined using the PDSs of the device and its frontand back-end matching two-ports are characterized by the scatteringparameters using the novel SRFT for each design target. Furthermore, the performances of the resulted amplifier circuits are analyzed and compared with the simulated results.

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“…This device characterization problem is solved point by point in [4,5] on the rigorous mathematical bases throughout the operation domain within the physical limitations of the employed device. Then, combining this performance characterization with the Artificial Neural Networks (ANN) or Support Vector Regression Machine (SVRM) model of the device [6,7], the compatible [F, V i , G T ] triplets together with their source Z S and load Z L terminations can be obtained as the functions of the operation variables V DS , I DS , f of the device (Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

Design of an Ultra-Wideband, Low-Noise Amplifier Using a Single Transistor: A Typical Application Example

Demi̇rel¹,

Güneş²,

Ozkaya³

2009

PIER B

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Abstract-In this work, a design method of an Ultra-Wideband (UWB), low-noise amplifier (LNA) is proposed exerting the performance limitations of a single high-quality discrete transistor. For this purpose, the compatible (Noise F , Input VSWR V i , Gain G T ) triplets and their (Z S , Z L ) terminations of a microwave transistor are exploited for the feasible design target space with the minimum noise F min (f ), maximum gain G T max (f ) and a low input VSWR V i over the available bandwidth B. This multi-objective design procedure is reduced into syntheses of the Darlington equivalences of the Z Sopt (f ), Z L max (f ) terminations with the Unit-elements and short-circuited stubs in the T -, L-, Π-configurations and Particle Swarm Intelligence is successfully implemented as a comparatively simple and efficient optimization tool into both verification of the design target space and the design process of the input and output matching circuits. A typical design example is given with its challenging performance in the simple Π-and Π-configurations realizable by the microstrip line technology. Furthermore the performances of the synthesized amplifiers are compared using an analysis programme in MATLAB code and a microwave system simulator and verified to agree with each other.

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Signal-noise support vector model of a microwave transistor

Cited by 38 publications

References 15 publications

Knowledge-Based Support Vector Synthesis of the Microstrip Lines

Knowledge-Based Support Vector Synthesis of the Microstrip Lines

A Generalized Design Procedure for a Microwave Amplifier: A Typical Application Example

Design of an Ultra-Wideband, Low-Noise Amplifier Using a Single Transistor: A Typical Application Example

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